Triple
T26203654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2017 New Jersey gubernatorial election |
E655301
|
entity |
| Predicate | lieutenantGovernorAfterElection |
P160038
|
FINISHED |
| Object | Sheila Oliver |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Sheila Oliver | Statement: [2017 New Jersey gubernatorial election, lieutenantGovernorAfterElection, Sheila Oliver]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lieutenantGovernorAfterElection Context triple: [2017 New Jersey gubernatorial election, lieutenantGovernorAfterElection, Sheila Oliver]
-
A.
governorAfterElection
Indicates that one entity serves as the governor of a region or jurisdiction following a specified election event.
-
B.
lieutenantGovernorElected
chosen
Indicates that an individual attains the position of lieutenant governor through an electoral process.
-
C.
incumbentAfterElection
Indicates that an entity holds a position or office as the sitting incumbent following a specified election.
-
D.
vicePresidentAfterElection
Indicates that one person holds the office of vice president following a specified election or electoral event.
-
E.
afterElectionSenator
Indicates that one person holds the position of senator following a specified election.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ee5b48236c81908fe385b6afc4f60b |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f60cdd664c8190862fe9543ab251c9 |
completed | May 2, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69f602d07590819085ac34b189613104 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 26, 2026, 8:49 p.m.